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R2075/DeconvolutionLab2/src/deconvolution/capsule/AlgorithmCapsule.java
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AlgorithmCapsule.java
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/*
* DeconvolutionLab2
*
* Conditions of use: You are free to use this software for research or
* educational purposes. In addition, we expect you to include adequate
* citations and acknowledgments whenever you present or publish results that
* are based on it.
*
* Reference: DeconvolutionLab2: An Open-Source Software for Deconvolution
* Microscopy D. Sage, L. Donati, F. Soulez, D. Fortun, G. Schmit, A. Seitz,
* R. Guiet, C. Vonesch, M Unser, Methods of Elsevier, 2017.
*/
/*
* Copyright 2010-2017 Biomedical Imaging Group at the EPFL.
*
* This file is part of DeconvolutionLab2 (DL2).
*
* DL2 is free software: you can redistribute it and/or modify it under the
* terms of the GNU General Public License as published by the Free Software
* Foundation, either version 3 of the License, or (at your option) any later
* version.
*
* DL2 is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License along with
* DL2. If not, see <http://www.gnu.org/licenses/>.
*/
package deconvolution.capsule;
import java.awt.Point;
import java.awt.Rectangle;
import javax.swing.JSplitPane;
import javax.swing.JViewport;
import signal.ComplexSignal;
import signal.RealSignal;
import signal.SignalCollector;
import bilib.component.HTMLPane;
import bilib.table.CustomizedTable;
import bilib.tools.NumFormat;
import deconvolution.Deconvolution;
import deconvolution.Features;
import deconvolution.algorithm.Algorithm;
import deconvolution.algorithm.AlgorithmList;
import deconvolution.algorithm.AlgorithmPanel;
import deconvolutionlab.monitor.Monitors;
import fft.AbstractFFT;
import fft.FFT;
/**
* This class is a information module for the algorithm.
*
* @author Daniel Sage
*
*/
public class AlgorithmCapsule extends AbstractCapsule implements Runnable {
private CustomizedTable table;
private HTMLPane doc;
public AlgorithmCapsule(Deconvolution deconvolution) {
super(deconvolution);
doc = new HTMLPane(100, 100);
table = new CustomizedTable(new String[] { "Features", "Values" }, false);
split = new JSplitPane(JSplitPane.VERTICAL_SPLIT, table.getPane(100, 100), doc.getPane());
split.setDividerLocation(0.5);
}
@Override
public void update() {
if (doc == null)
return;
if (table == null)
return;
table.removeRows();
table.append(new String[] { "PSF", "Waiting for loading ..." });
Thread thread = new Thread(this);
thread.setPriority(Thread.MIN_PRIORITY);
thread.start();
}
@Override
public String getID() {
return "Algorithm";
}
@Override
public void run() {
Features features = new Features();
if (deconvolution.getAlgorithm() == null) {
features.add("Algorithm", "No valid algorithm");
return;
}
Algorithm algo = deconvolution.getAlgorithm();
doc.clear();
String name = algo.getShortnames()[0];
AlgorithmPanel algoPanel = AlgorithmList.getPanel(name);
if (algoPanel != null)
doc.append(algoPanel.getDocumentation());
String p = algo.getParametersAsString();
features.add("<html><b>Parameters</b></html>", p.equals("") ? "Parameters free" : p);
features.add("Iteration", algo.isIterative() ? "" + algo.getIterationsMax() : "Direct");
if (deconvolution.image == null) {
startAsynchronousTimer("Open image", 200);
deconvolution.image = deconvolution.openImage();
stopAsynchronousTimer();
}
if (deconvolution.image == null) {
features.add("Image", "No valid input image");
return;
}
if (deconvolution.getController().getPadding() == null) {
features.add("Padding", "No valid padding");
return;
}
if (deconvolution.getController().getApodization() == null) {
features.add("Apodization", "No valid apodization");
return;
}
if (deconvolution.psf == null) {
startAsynchronousTimer("Open PSF", 200);
deconvolution.psf = deconvolution.openPSF();
stopAsynchronousTimer();
}
if (deconvolution.psf == null) {
features.add("Image", "No valid PSF");
return;
}
startAsynchronousTimer("Check Algorithm", 200);
AbstractFFT f = FFT.getFastestFFT().getDefaultFFT();
double Q = Math.sqrt(2);
if (deconvolution.image != null) {
int mx = deconvolution.image.nx;
int my = deconvolution.image.ny;
int mz = deconvolution.image.nz;
while (mx * my * mz > Math.pow(2, 15)) {
mx = (int)(mx / Q);
my = (int)(my / Q);
mz = (int)(mz / Q);
}
double N = deconvolution.image.nx * deconvolution.image.ny * deconvolution.image.nz;
double M = mx * my * mz;
double ratio = 1;
if (M != 0)
ratio = (N * Math.log(N)) / (M * Math.log(M));
double chrono = System.nanoTime();
RealSignal x = new RealSignal("test", mx, my, mz);
ComplexSignal c = new ComplexSignal("test", mx, my, mz);
f.init(Monitors.createDefaultMonitor(), mx, my, mz);
f.transform(x, c);
SignalCollector.free(x);
SignalCollector.free(c);
chrono = (System.nanoTime() - chrono);
double chronoI = chrono * ratio * algo.getComplexityNumberofFFT();
features.add("<html><b>Estimation</b></html>", "");
features.add("Estimated time", NumFormat.time(chronoI) );
features.add("Estimated number of FFTs", "" + algo.getComplexityNumberofFFT());
features.add("<html><b>Run on tiny dataset</b></html>", mx + "x" + my + "x" + mz);
features.add("Elapsed time", NumFormat.time(chrono) );
}
else
features.add("Estimated time", "Error" );
double mem = (algo.getMemoryFootprintRatio() * deconvolution.image.nx * deconvolution.image.ny * deconvolution.image.nz * 4);
features.add("Required memory", NumFormat.bytes(mem));
table.removeRows();
for (String[] feature : features)
table.append(feature);
Rectangle rect = table.getCellRect(0, 0, true);
Point pt = ((JViewport) table.getParent()).getViewPosition();
rect.setLocation(rect.x - pt.x, rect.y - pt.y);
stopAsynchronousTimer();
}
}
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